Voids or other defects in an insulation material may give rise to non-homogeneous electric fields in the material. In that connection, the field strength may become so high that a local discharge, a partial discharge, in the material occurs. A general description of these phenomena is given, for example, in E. Kuffel, W. S. Zaengl: High Voltage Engineering, Pergamon Press, 1984.
Conventionally, partial discharges are measured using a capacitive decoupling from the object to be measured and a detector unit, for example a bridge or a fast digital converter and a computer. In IEC Publication 270: "Partial Discharge Measurements", 1981, 2nd edition, normalized methods for such measurements and for calibration of the measurement equipment are discussed.
Measurement of partial discharges using inductive sensors based on Rogowski coils is described in Proceedings of the 1987 International Symposium on High Voltage Engineering, vol. 2, paper No. 42.02, H. Borsi, M. Hartje: "Application of Rogowski coils for Partial Discharge (PD), decoupling and noise suppression".
The occurrence of partial discharges in a high-voltage apparatus is often an indication that a fault is developing.
A power transformer is usually a critical component in a power network. An extensive fault in the transformer may cause long interruptions and expensive repairs. It is therefore desirable to discover states which may lead to faults as early as possible. A power transformer is often equipped with a capacitive test tap at its high-voltage bushings, which may be utilized as a capacitive decoupler. It is therefore also possible to carry out a conventional measurement of partial discharges under normal operating conditions.
A problem that arises during a measurement in a transformer station compared with a measurement in a test chamber environment are the disturbances that are generated by surrounding apparatus and connections. To cope with these external disturbances, different solutions have been proposed and tried, for example PRPDA and pattern recognition using neural networks. See, for example, descriptions in IEE Proc.-Science Measurement and Technology, vol. 142, No. 1, January 1995, pp. 22-28, B. A. Fruth, D. W. Gross: "Partial discharge signal generation transmission and acquisition", and in IEE Proc.-Science Measurement and Technology, vol. 142, No. 1, January 1995, pp. 69-74, H. Borsi, E. Gockenbach, D. Wenzel: "Separation of partial discharges from pulse-shaped noise signals with the help of neural networks". Both methods described in these publications are based on learning typical signal patterns. In an analysis according to the PRPDA method, data is collected over a certain period of time, whereupon the pattern for these data is compared with patterns for known types of discharges. Neural networks are taught to recognize the wave shape for certain specific types of discharges. For both of these methods, the decoupling of the partial discharges is carried out in a conventional manner.